# Array > Pseudorandom number generator (PRNG) array creation functions.
## Usage ```javascript var ns = require( '@stdlib/random/array' ); ``` #### ns Namespace containing array creation pseudorandom number generator (PRNG) functions. ```javascript var o = ns; // returns {...} ``` The namespace contains the following:
- [`arcsine( len, a, b[, options] )`][@stdlib/random/array/arcsine]: create an array containing pseudorandom numbers drawn from an arcsine distribution. - [`bernoulli( len, p[, options] )`][@stdlib/random/array/bernoulli]: create an array containing pseudorandom numbers drawn from a Bernoulli distribution. - [`beta( len, alpha, beta[, options] )`][@stdlib/random/array/beta]: create an array containing pseudorandom numbers drawn from a beta distribution. - [`betaprime( len, alpha, beta[, options] )`][@stdlib/random/array/betaprime]: create an array containing pseudorandom numbers drawn from a beta prime distribution. - [`binomial( len, n, p[, options] )`][@stdlib/random/array/binomial]: create an array containing pseudorandom numbers drawn from a binomial distribution. - [`cauchy( len, x0, gamma[, options] )`][@stdlib/random/array/cauchy]: create an array containing pseudorandom numbers drawn from a Cauchy distribution. - [`chi( len, k[, options] )`][@stdlib/random/array/chi]: create an array containing pseudorandom numbers drawn from a chi distribution. - [`chisquare( len, k[, options] )`][@stdlib/random/array/chisquare]: create an array containing pseudorandom numbers drawn from a chi-square distribution. - [`cosine( len, mu, s[, options] )`][@stdlib/random/array/cosine]: create an array containing pseudorandom numbers drawn from a raised cosine distribution. - [`discreteUniform( len, a, b[, options] )`][@stdlib/random/array/discrete-uniform]: create an array containing pseudorandom numbers drawn from a discrete uniform distribution. - [`erlang( len, k, lambda[, options] )`][@stdlib/random/array/erlang]: create an array containing pseudorandom numbers drawn from an Erlang distribution. - [`exponential( len, lambda[, options] )`][@stdlib/random/array/exponential]: create an array containing pseudorandom numbers drawn from an exponential distribution. - [`f( len, d1, d2[, options] )`][@stdlib/random/array/f]: create an array containing pseudorandom numbers drawn from an F distribution. - [`frechet( len, alpha, s, m[, options] )`][@stdlib/random/array/frechet]: create an array containing pseudorandom numbers drawn from a Fréchet distribution. - [`gamma( len, alpha, beta[, options] )`][@stdlib/random/array/gamma]: create an array containing pseudorandom numbers drawn from a gamma distribution. - [`geometric( len, p[, options] )`][@stdlib/random/array/geometric]: create an array containing pseudorandom numbers drawn from a geometric distribution. - [`gumbel( len, mu, beta[, options] )`][@stdlib/random/array/gumbel]: create an array containing pseudorandom numbers drawn from a Gumbel distribution. - [`hypergeometric( len, N, K, n[, options] )`][@stdlib/random/array/hypergeometric]: create an array containing pseudorandom numbers drawn from a hypergeometric distribution. - [`invgamma( len, alpha, beta[, options] )`][@stdlib/random/array/invgamma]: create an array containing pseudorandom numbers drawn from a inverse gamma distribution. - [`kumaraswamy( len, a, b[, options] )`][@stdlib/random/array/kumaraswamy]: create an array containing pseudorandom numbers drawn from Kumaraswamy's double bounded distribution. - [`laplace( len, mu, b[, options] )`][@stdlib/random/array/laplace]: create an array containing pseudorandom numbers drawn from a Laplace (double exponential) distribution. - [`levy( len, mu, c[, options] )`][@stdlib/random/array/levy]: create an array containing pseudorandom numbers drawn from a Lévy distribution. - [`logistic( len, mu, s[, options] )`][@stdlib/random/array/logistic]: create an array containing pseudorandom numbers drawn from a logistic distribution. - [`lognormal( len, mu, sigma[, options] )`][@stdlib/random/array/lognormal]: create an array containing pseudorandom numbers drawn from a lognormal distribution. - [`minstdShuffle( len[, options] )`][@stdlib/random/array/minstd-shuffle]: create an array containing pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG) whose output is shuffled. - [`minstd( len[, options] )`][@stdlib/random/array/minstd]: create an array containing pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG). - [`mt19937( len[, options] )`][@stdlib/random/array/mt19937]: create an array containing pseudorandom numbers generated using a 32-bit Mersenne Twister pseudorandom number generator. - [`negativeBinomial( len, r, p[, options] )`][@stdlib/random/array/negative-binomial]: create an array containing pseudorandom numbers drawn from a negative binomial distribution. - [`normal( len, mu, sigma[, options] )`][@stdlib/random/array/normal]: create an array containing pseudorandom numbers drawn from a normal distribution. - [`pareto1( len, alpha, beta[, options] )`][@stdlib/random/array/pareto-type1]: create an array containing pseudorandom numbers drawn from a Pareto (Type I) distribution. - [`poisson( len, lambda[, options] )`][@stdlib/random/array/poisson]: create an array containing pseudorandom numbers drawn from a Poisson distribution. - [`randu( len[, options] )`][@stdlib/random/array/randu]: create an array containing uniformly distributed pseudorandom numbers between `0` and `1`. - [`rayleigh( len, sigma[, options] )`][@stdlib/random/array/rayleigh]: create an array containing pseudorandom numbers drawn from a Rayleigh distribution. - [`t( len, v[, options] )`][@stdlib/random/array/t]: create an array containing pseudorandom numbers drawn from a Student's t-distribution. - [`triangular( len, a, b, c[, options] )`][@stdlib/random/array/triangular]: create an array containing pseudorandom numbers drawn from a triangular distribution. - [`uniform( len, a, b[, options] )`][@stdlib/random/array/uniform]: create an array containing pseudorandom numbers drawn from a continuous uniform distribution. - [`weibull( len, k, lambda[, options] )`][@stdlib/random/array/weibull]: create an array containing pseudorandom numbers drawn from a Weibull distribution.
## Examples ```javascript var ns = require( '@stdlib/random/array' ); // Generate arrays with ten random numbers drawn from the respective distributions: var out = ns.arcsine( 10, 2.0, 5.0 ); // returns out = ns.weibull( 10, 2.0, 5.0 ); // returns out = ns.laplace( 10, 2.0, 5.0 ); // returns // Factory methods: // 1. Basic factory usage (no parameters): var random = ns.arcsine.factory(); out = random( 10, 2.0, 5.0 ); // returns // 2. Factory with options (e.g., seed): random = ns.arcsine.factory({ 'seed': 1234 }); out = random( 10, 2.0, 5.0 ); // returns // 3. Factory with distribution parameters: random = ns.arcsine.factory( 2.0, 5.0 ); out = random( 10 ); // returns // 4. Factory with both distribution parameters and options: random = ns.arcsine.factory( 2.0, 5.0, { 'dtype': 'float32' }); out = random( 10 ); // returns ```
[@stdlib/random/array/arcsine]: https://github.com/stdlib-js/random/tree/main/array/arcsine [@stdlib/random/array/bernoulli]: https://github.com/stdlib-js/random/tree/main/array/bernoulli [@stdlib/random/array/beta]: https://github.com/stdlib-js/random/tree/main/array/beta [@stdlib/random/array/betaprime]: https://github.com/stdlib-js/random/tree/main/array/betaprime [@stdlib/random/array/binomial]: https://github.com/stdlib-js/random/tree/main/array/binomial [@stdlib/random/array/cauchy]: https://github.com/stdlib-js/random/tree/main/array/cauchy [@stdlib/random/array/chi]: https://github.com/stdlib-js/random/tree/main/array/chi [@stdlib/random/array/chisquare]: https://github.com/stdlib-js/random/tree/main/array/chisquare [@stdlib/random/array/cosine]: https://github.com/stdlib-js/random/tree/main/array/cosine [@stdlib/random/array/discrete-uniform]: https://github.com/stdlib-js/random/tree/main/array/discrete-uniform [@stdlib/random/array/erlang]: https://github.com/stdlib-js/random/tree/main/array/erlang [@stdlib/random/array/exponential]: https://github.com/stdlib-js/random/tree/main/array/exponential [@stdlib/random/array/f]: https://github.com/stdlib-js/random/tree/main/array/f [@stdlib/random/array/frechet]: https://github.com/stdlib-js/random/tree/main/array/frechet [@stdlib/random/array/gamma]: https://github.com/stdlib-js/random/tree/main/array/gamma [@stdlib/random/array/geometric]: https://github.com/stdlib-js/random/tree/main/array/geometric [@stdlib/random/array/gumbel]: https://github.com/stdlib-js/random/tree/main/array/gumbel [@stdlib/random/array/hypergeometric]: https://github.com/stdlib-js/random/tree/main/array/hypergeometric [@stdlib/random/array/invgamma]: https://github.com/stdlib-js/random/tree/main/array/invgamma [@stdlib/random/array/kumaraswamy]: https://github.com/stdlib-js/random/tree/main/array/kumaraswamy [@stdlib/random/array/laplace]: https://github.com/stdlib-js/random/tree/main/array/laplace [@stdlib/random/array/levy]: https://github.com/stdlib-js/random/tree/main/array/levy [@stdlib/random/array/logistic]: https://github.com/stdlib-js/random/tree/main/array/logistic [@stdlib/random/array/lognormal]: https://github.com/stdlib-js/random/tree/main/array/lognormal [@stdlib/random/array/minstd-shuffle]: https://github.com/stdlib-js/random/tree/main/array/minstd-shuffle [@stdlib/random/array/minstd]: https://github.com/stdlib-js/random/tree/main/array/minstd [@stdlib/random/array/mt19937]: https://github.com/stdlib-js/random/tree/main/array/mt19937 [@stdlib/random/array/negative-binomial]: https://github.com/stdlib-js/random/tree/main/array/negative-binomial [@stdlib/random/array/normal]: https://github.com/stdlib-js/random/tree/main/array/normal [@stdlib/random/array/pareto-type1]: https://github.com/stdlib-js/random/tree/main/array/pareto-type1 [@stdlib/random/array/poisson]: https://github.com/stdlib-js/random/tree/main/array/poisson [@stdlib/random/array/randu]: https://github.com/stdlib-js/random/tree/main/array/randu [@stdlib/random/array/rayleigh]: https://github.com/stdlib-js/random/tree/main/array/rayleigh [@stdlib/random/array/t]: https://github.com/stdlib-js/random/tree/main/array/t [@stdlib/random/array/triangular]: https://github.com/stdlib-js/random/tree/main/array/triangular [@stdlib/random/array/uniform]: https://github.com/stdlib-js/random/tree/main/array/uniform [@stdlib/random/array/weibull]: https://github.com/stdlib-js/random/tree/main/array/weibull